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Four Sliding Windows Pattern Matching algorithm (FSW)

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Journal of Software Engineering and Applications 2015年第3期8卷 154-165页

作者： Amjad Hudaib Rola al-Khalid aseel al-anani Mariam Itriq Dima Suleiman Department of Computer Information Systems King Abdullah II School for Information Technology The University of Jordan Amman Jordan Department of Business Information Technology King Abdullah II School for Information Technology The University of Jordan Amman Jordan

This paper presents an efficient pattern matching algorithm (FSW). FSW improves the searching process for a pattern in a text. It scans the text with the help of four sliding windows. The windows are equal to the length of the pattern, allowing multiple alignments in the searching process. The text is divided into two parts;each part is scanned from both sides simultaneously using two sliding windows. The four windows slide in parallel in both parts of the text. The comparisons done between the text and the pattern are done from both of the pattern sides in parallel. The conducted experiments show that FSW achieves the best overall results in the number of attempts and the number of character comparisons compared to the pattern matching algorithms: Two Sliding Windows (TSW), Enhanced Two Sliding Windows algorithm (ETSW) and Berry-Ravindran algorithm (BR). The best time case is calculated and found to be??while the average case time complexity is??.

关键词： Pattern Matching FWS Enhanced Two Sliding Windows algorithm RS-A Fast Pattern Matching algorithm

Asphaltene onset pressure measurement and calculation techniques:A review

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Petroleum 2024年第2期10卷 191-201页

作者： Sherif Fakher Amr Yousef aseel al-Sakkaf Shams Eldakar Petroleum and Energy Engineering The American University in CairoCairoEgyp

Asphaltene precipitation can result in several production,operational,and transportation problems during oil *** asphaltene precipitates and deposits,it can reduce reservoir permeability,damage wellbore equipment,and plug the *** is therefore extremely important to evaluate the conditions at which asphaltene precipitation occurs;this is referred to as the asphaltene onset *** onset pressure has been measured using many different experimental *** have also been many attempts along the years to predict asphaltene onset pressure using mathematical correlations and *** research provides an up-to-date comprehensive review of the methods by which asphaltene onset pressure can be measured using laboratory experiments and mathematical *** research explains the main mechanisms of all the laboratory experiments to measure asphaltene onset pressure under static conditions and how to conduct them and highlights the advantages and limitations of each *** research also provides a summary of the commonly used mathematical models to quantify asphaltene onset pressure directly and indirectly.

关键词： Asphaltene onset measurement

A Secure Visual Cryptography Scheme Using Private Key with Invariant Share Sizes

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Journal of Software Engineering and Applications 2017年第1期10卷 1-10页

作者： Rola I. al-Khalid Randa A. al-Dallah aseel M. al-anani Raghad M. Barham Salam I. Hajir Department of Computer Information Systems King Abdullah II School for Information Technology The University of Jordan Amman Jordan Department of Computer and Networks Engineering Faculty of Engineering Technology Al-Balqa’ Applied University Amman Jordan

Visual cryptography (VC) is one of the best techniques used to secure information. It uses the human vision to decrypt the encrypted images without any cryptographic computations. The basic concept of visual cryptography is splitting the secret image into shares such that when the shares are stacked, the secret image is revealed. In this paper we proposed a method that is based on the concept of visual cryptography for color images and without any pixel expansion which requires less space. The proposed method is used to encrypt halftone color images by generating two shares, random and key shares which are the same size as the secret color image. The two shares are generated based on a private key. At the receiving side, the secret color image is revealed by stacking the two shares and exploiting the human vision system. In this paper, we produce an enhanced form of the proposed method by modifying the encryption technique used to generate the random and the key shares. Experimental results have shown that the proposed and the enhanced methods suggest an efficient way to encrypt a secret color image with better level of security, less storage space, less time of computation and with a better value of PSNR.

关键词： Visual Cryptography (VC) Halftone Color Images Pixel Expansion PSNR Private Key

Detection of Knowledge on Social Media Using Data Mining Techniques

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Open Journal of Applied Sciences 2024年第2期14卷 472-482页

作者： aseel Abdullah alolayan Ahmad A. alhamed Department of Information Systems King Saud University Riyadh Saudi Arabia

In light of the rapid growth and development of social media, it has become the focus of interest in many different scientific fields. They seek to extract useful information from it, and this is called (knowledge), such as extracting information related to people’s behaviors and interactions to analyze feelings or understand the behavior of users or groups, and many others. This extracted knowledge has a very important role in decision-making, creating and improving marketing objectives and competitive advantage, monitoring events, whether political or economic, and development in all fields. Therefore, to extract this knowledge, we need to analyze the vast amount of data found within social media using the most popular data mining techniques and applications related to social media sites.

关键词： Data Mining Knowledge Data Mining Techniques Social Media

Single image super-resolution:a comprehensive review and recent insight

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Frontiers of Computer Science 2024年第1期18卷 139-156页

作者： Hanadi al-MEKHLAFI Shiguang LIU College of Intelligence and Computing Tianjin UniversityTianjin 300350China

Super-resolution(SR)is a long-standing problem in image processing and computer vision and has attracted great attention from researchers over the *** main concept of SR is to reconstruct images from low-resolution(LR)to high-resolution(HR).It is an ongoing process in image technology,through up-sampling,de-blurring,and *** neural network(CNN)has been widely used to enhance the resolution of images in recent *** alternative methods use deep learning to improve the progress of image super-resolution based on ***,we review the recent findings of single image super-resolution using deep learning with an emphasis on distillation knowledge used to enhance image super-resolution.,it is also to highlight the potential applications of image super-resolution in security monitoring,medical diagnosis,microscopy image processing,satellite remote sensing,communication transmission,the digital multimedia industry and video ***,we present the challenges and assess future trends in super-resolution based on deep learning.

关键词： super-resolution deep learning single-image interpolation-based learning-based reconstruction-based

RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

作者： Farah Mohammad Saad al-Ahmadi Jalal al-Muhtadi Center of Excellence in Information Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of Computer&Information Sciences King Saud UniversityRiyadh11543Saudi Arabia

Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by *** development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious *** key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification *** performance evaluation of the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

关键词： Electricity theft smart grid RoBERTa GRU transfer learning

Developing a Model for Parkinson’s Disease Detection Using Machine Learning algorithms

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Computers, Materials & Continua 2024年第6期79卷 4945-4962页

作者： Naif al Mudawi Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia

Parkinson’s disease(PD)is a chronic neurological condition that progresses over *** start to have trouble speaking,writing,walking,or performing other basic skills as dopamine-generating neurons in some brain regions are injured or *** patient’s symptoms become more severe due to the worsening of their signs over *** this study,we applied state-of-the-art machine learning algorithms to diagnose Parkinson’s disease and identify related risk *** research worked on the publicly available dataset on PD,and the dataset consists of a set of significant characteristics of *** aim to apply soft computing techniques and provide an effective solution for medical professionals to diagnose PD *** research methodology involves developing a model using a machine learning *** the model selection,eight different machine learning techniques were adopted:Namely,Random Forest(RF),Decision Tree(DT),Support Vector Machine(SVM),Naïve Bayes(NB),Light Gradient Boosting Machine(LightGBM),K-Nearest Neighbours(KNN),Extreme Gradient Boosting(XGBoost),and Logistic Regression(LR).Subsequently,the concentrated models were validated through 10-fold Cross-Validation and Receiver Operating Characteristic(ROC)—Area Under the Curve(AUC).In addition,GridSearchCV was utilised to measure each algorithm’s best parameter;eventually,the models were trained through the hyperparameter tuning *** 98%accuracy,LightGBM had the highest accuracy in this ***,KNN,and SVM came in second with 96%***,the performance scores of NB and LR were recorded to be 76%and 83%,*** is to be mentioned that after applying 10-fold cross-validation,the average performance score of LightGBM accounted for 93%.At the same time,the percentage of ROC-AUC appeared at 0.92,which indicates that this LightGBM model reached a satisfactory ***,we extracted meaningful insights and figured out potential gaps on top of *** extracting meaningful in

关键词： Light GBM cross-validation ROC-AUC Parkinson’s disease(PD) SVM and XGBoost

The optimal semi-analytical modeling for the infinite-conductivity horizontal well performance under rectangular bounded reservoir based on a new instantaneous source function

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Petroleum 2024年第1期10卷 68-84页

作者： Firas A.A.al-Kabbawi Independent scholar LivingstonScotlandUNITED KINGDOM

The main objective of this study is to develop the optimal semi-analytical modeling for the infiniteconductivity horizontal well performance under rectangular bounded reservoir based on a new instantaneous source *** available semi-analytical infinite-conductivity models(ICMs)for horizontal well under rectangular bounded reservoir in literature were developed by applying superposition of pressures in space(SPS).A new instantaneous source function(i.e.,instantaneous uniform-flux segmentary source function under bounded reservoir)is derived to be used instead of SPS to develop the optimal semi-analytical *** new semi-analytical ICM is verified with ICM of Schlumberger[1]and with previous semi-analytical ICMs in terms of bottom hole pressure(BHP)profile and inflow rate distribution along the *** model is also validated with real horizontal wells in terms of inflow rate distribution along the *** results show that the developed model gives the optimal semi-analytical modeling for the infinite-conductivity horizontal well performance under rectangular bounded *** that,high computationalefficiency and high-resolution of wellbore discretization have been achieved(i.e.,wellbore segment number could be tens of hundreds depending on solution requirement).The results also show that at pseudosteady state(PSS)flow regime,inflow rate distribution along the wellbore by previous semi-analytical ICMs is stabilized U-shaped as performance of inflow rate distribution at late radial flow ***,the previous semi-analytical ICMs are incorrectly modeling inflow rate distribution at PSS flow regime due to the negative influence of applying *** optimal semi-analytical ICM is in a general form and real time domain,and can be applicable for 3D horizontal well and 2D vertical fracture well under infinite and rectangular bounded reservoirs,of uniform-flux and infinite-conductivity wellbore conditions at any time of well life.

关键词： Infinite-conductivity model Horizontal well performance Semi-analytical modeling Rectangular bounded reservoir Instantaneous source functions Flow regimes

Degradation pathways of amino acids during thermal utilization of biomass: a review

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Frontiers of Chemical Science and Engineering 2024年第7期18卷 67-95页

作者： Mubarak al-Kwradi Mohammednoor altarawneh Department of Chemical and Petroleum Engineering United Arab Emirates UniversityAl-Ain 15551United Arab Emirates

Amino acids are important nitrogen carriers in biomass and entail a broad spectrum of industrial uses,most notably as food additives,pharmaceutical ingredients,and raw materials for bio-based *** detailed information in regard to the fragmentation of amino acids is essential to comprehend the nitrogen transformation chemistry at conditions encountered during hydrothermal and pyrolytic degradation of *** underlying aim of this review is to survey literature studies pertinent to the complex structures of amino acids,their formation yields from various categories of biomass,and their fragmentation routes at elevated temperatures and in the aqueous *** predominant degradation reactions ensue in the decomposition of amino acids,namely deamination and ***,minor differences in structure can greatly affect the fate for each amino ***,amino acids,being nitrogen-rich compounds,play pivotal roles across various *** is a growing interest in producing varied types and configurations of amino *** fermentation appears to a viable approach to produce amino acids at an industrial *** innovative method under investigation is catalytic synthesis using renewable biomass as *** a method taps into the inherent nitrogen in biomass sources like chitin and proteins,eliminating the need for external nitrogen *** environmentally friendly approach is in line with green chemistry principles and has been gathering momentum in the scientific community.

关键词： amino acids pyrolysis biomass nitrogen mechanisms bioenergy